SSRS - Count values in a column based upon distinct values in another column in SharePoint List
By : Jurc
Date : March 29 2020, 07:55 AM
wish help you to fix your issue You can use matrix to easily achieve this. Use Column A (red, blue, green) for column grouping code :
=SUM(IIF(ISNOTHING(Fields!ColumnA.VALUE) OR ISNOTHING(Fields!ColumnB.VALUE), 0, 1)
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PHP Average values in column based on year date
By : Standford Reid
Date : March 29 2020, 07:55 AM
this will help Im working on webpage that should average values in a given column based on the current year. Ive got the following code: , You basically answered the question yourself: code :
$year = date("Y");
$year = "$year%";
$stmt = $this->dbconn->prepare("SELECT AVG(ElecUsage), DateAdded FROM
elec_readings WHERE AccountNumber = '" . $_SESSION['user_session'] . "'
AND DateAdded LIKE '$year'");
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Dynamically select a column using month and year, then sumif the values based on criteria in another column
By : Silvestre Gil
Date : March 29 2020, 07:55 AM
I hope this helps . I would "cheat" I have my months list was in AI1:AI12, and year list in AJ1:AJ2 (for the dropdowns in A1 and B1 respectively). Move them elsewhere for more years. code :
=MATCH(A1,AI1:AI12,0)
=IF(MATCH(B1,AJ1:AJ2,0)=1,0,12 *( MATCH(B1,AJ1:AJ2,0)-1))
=SUMIF($C$3:$C$8,"Plan",D3:D8)
=OFFSET(D10,,B2+A2-1,1,1)
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Count the number of times two values appear in a column based on the unique values of another column
By : Julija Wilson
Date : November 01 2020, 04:01 AM
should help you out We can use count and spread to get the df format and use fill = 0 in spread to fill in the 0s: code :
library(tidyverse)
YG %>%
group_by(year) %>%
count(gender) %>%
spread(gender, n, fill = 0)
# A tibble: 3 x 3
# Groups: year [3]
year F M
<fct> <dbl> <dbl>
1 2000 1 2
2 2001 0 1
3 2002 1 0
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Cumulative count based on year column in pandas
By : Kaito002
Date : March 29 2020, 07:55 AM
hop of those help? I have a data frame as shown below , you can try this: code :
df_new = df.groupby(['Unit_Create_Year']).agg({'Unit_ID':['count','unique']}).reset_index()
df_new.columns = ['Year','Number_of_Unit_Since_Year','List_of_Units']
df_new['Number_of_Unit_Since_Year'] = df_new['Number_of_Unit_Since_Year'].cumsum()
df_new['List_of_Units'] = df_new['List_of_Units'].apply(lambda x : x.tolist()).cumsum()
df_new
Year Number_of_Unit_Since_Year List_of_Units
0 2011 2 [1, 2]
1 2012 4 [1, 2, 3, 5]
2 2014 5 [1, 2, 3, 5, 4]
3 2015 6 [1, 2, 3, 5, 4, 6]
4 2017 9 [1, 2, 3, 5, 4, 6, 7, 8, 9]
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